161 to 170 of 184 Results
Sep 2, 2019 -
Lexicon of Abusive Words (EN)
ZIP Archive - 738.4 KB -
MD5: 46f33f5b7a9c866b1a2fb6dc956b945d
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Sep 2, 2019 -
Lexicon of Abusive Words (EN)
Markdown Text - 4.4 KB -
MD5: 3cbbac5ff1534a6e9c3fcc9a1b0be976
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Sep 2, 2019
Wiegand, Michael, 2019, "Opinion role extractor", https://doi.org/10.11588/data/3W7AQP, heiDATA, V1
System for the Extraction of Subjective Expressions, Sentiment Sources and Sentiment Targets from German Text |
Sep 2, 2019 -
Opinion role extractor
ZIP Archive - 20.8 MB -
MD5: 6704c06c5a8566eb05c3a8e0e0baebc2
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Sep 2, 2019 -
Opinion role extractor
Plain Text - 13.0 KB -
MD5: c4eb5b271a38da142c703216f9648f09
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Aug 23, 2019
van den Berg, Esther; Korfhage, Katharina; Ruppenhofer, Josef; Wiegand, Michael; Markert, Katja, 2019, "Twitter Titling Corpus", https://doi.org/10.11588/data/IOHXDF, heiDATA, V1, UNF:6:+F3lLKziwMvjy+xyktkilw== [fileUNF]
The Twitter Titling Corpus contains 4002 stance-annotated tweets collected between 20 June 2017 and 30 August 2017 mentioning 6 presidents. Each tweet is annotated for the naming form used to refer to the president, for the purpose of a study on the relation between naming variat... |
Aug 23, 2019 -
Twitter Titling Corpus
Tabular Data - 219.0 KB - 5 Variables, 4002 Observations - UNF:6:+F3lLKziwMvjy+xyktkilw==
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Aug 19, 2019
Kotnis, Bhushan, 2019, "Negative Sampling for Learning Knowledge Graph Embeddings", https://doi.org/10.11588/data/YYULL2, heiDATA, V1
Reimplementation of four KG factorization methods and six negative sampling methods. Abstract Knowledge graphs are large, useful, but incomplete knowledge repositories. They encode knowledge through entities and relations which define each other through the connective structure o... |
Aug 19, 2019 -
Negative Sampling for Learning Knowledge Graph Embeddings
ZIP Archive - 19.4 KB -
MD5: d2e8ac74e3f20d2cdec2225962c7e2f0
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Aug 19, 2019
Kotnis, Bhushan, 2019, "KGE Algorithms", https://doi.org/10.11588/data/CSXYSS, heiDATA, V1
An updated method for link prediction that uses a regularization factor that models relation argument types Abstract (Kotnis and Nastase, 2017): Learning relations based on evidence from knowledge repositories relies on processing the available relation instances. Knowledge repos... |